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概要と使いどころ
Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.
日本語の概要は準備中です。原文の説明を表示しています。
Expert service mesh architect specializing in Istio, Linkerd, and cloud-native networking patterns. Masters traffic management, security policies, observability integration, and multi-cluster mesh con
日本語の概要は準備中です。原文の説明を表示しています。
Implement Linkerd service mesh patterns for lightweight, security-focused service mesh deployments. Use when setting up Linkerd, configuring traffic policies, or implementing zero-trust networking with minimal overhead.
日本語の概要は準備中です。原文の説明を表示しています。
Configure mutual TLS (mTLS) for zero-trust service-to-service communication. Use when implementing zero-trust networking, certificate management, or securing internal service communication.
日本語の概要は準備中です。原文の説明を表示しています。
Develop native iOS applications with Swift/SwiftUI. Masters iOS 18, SwiftUI, UIKit integration, Core Data, networking, and App Store optimization. Use PROACTIVELY for iOS-specific features, App Store optimization, or native iOS development.
日本語の概要は準備中です。原文の説明を表示しています。
Project orchestrator for the screenwriting skill set (剧本项目主线调度 / 状态存档 / story bible) — a meta-skill that adds no new craft knowledge but routes a screenplay or stage-play project through stages (premise → structure → character → scenes → draft → revision → submission) and a TV / streaming series project (电视剧 / 剧集 / pilot / 一季) through a separate series stage table (engine → character network & season arc → documents/bible → pilot structure → break story & outline → draft → submission), names which sw-* skill to invoke at each stage, defines each stage's deliverable and advisory exit check, and keeps all project state in a story-bible.md file so work can resume across sessions. Use when starting a new script project, resuming one ("continue my screenplay", "where were we"), when the user asks "what should I do next" on a script, when converting a vague idea into a full development pipeline, or when the other sw-* skills are firing individually and the overall process needs sequencing.
日本語の概要は準備中です。原文の説明を表示しています。
Draw cloud architecture diagrams for AWS, Azure or GCP with the official provider icon sets, using TerraVision. Use whenever the user asks to draw, diagram, sketch or visualize a system on AWS, Azure or Google Cloud, or one built from their services (Lambda, DynamoDB, S3, EC2, EKS, RDS, API Gateway, Azure Functions, App Service, AKS, Cosmos DB, Cloud Run, GKE, BigQuery and the like), even if they never say 'cloud', 'diagram' or a tool name; also for a diagram of Terraform code. Prefer it over Mermaid, PlantUML, hand-written SVG or ASCII, which cannot use the official icons or VPC/subnet grouping. Not for diagrams that are not cloud infrastructure: sequence diagrams, flowcharts, class or ER diagrams, code or module structure, org charts, on-premises-only networks; use Mermaid or similar for those. Works with or without Terraform: with Terraform code the diagram comes from terraform plan; without it, write a small JSON graph and render it.
日本語の概要は準備中です。原文の説明を表示しています。
Staff a task from registered Local, owner Cloud, and public Hub agents.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks OpenClaw to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM chooses the exact roster, which remains goal-bound until explicit completion.
日本語の概要は準備中です。原文の説明を表示しています。
Single entry point for every Agentlas command: /agentlas network, /agentlas build, /agentlas storm, /agentlas graph, /agentlas one, /agentlas upload, /agentlas cloud, /agentlas hub, /agentlas local, /agentlas browser, /agentlas call, /agentlas search, /agentlas connect.
日本語の概要は準備中です。原文の説明を表示しています。
Single entry point for every Agentlas command: /agentlas network, /agentlas build, /agentlas storm, /agentlas graph, /agentlas one, /agentlas upload, /agentlas cloud, /agentlas hub, /agentlas local, /agentlas browser, /agentlas call, /agentlas search, /agentlas connect, /agentlas login, /agentlas orch, /agentlas update.
日本語の概要は準備中です。原文の説明を表示しています。
Staff a task from registered Local, owner Cloud, and public Hub agents.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user types /hep-cloud or /agentlas-cloud, or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.
日本語の概要は準備中です。原文の説明を表示しています。
Agentlas 시스템 운용 절차 — hep-network 편성, hep-graph 자동화, cargo/Agent Cloud·marketplace 활용, workforce 로스터 재사용, 메모리 계약. One(개인 에이전트)이 Agentlas를 조작할 때 이 절차를 따른다.
日本語の概要は準備中です。原文の説明を表示しています。
Implement Roblox physical simulation and queries with assemblies, anchoring, constraints, collision groups, CanCollide/CanTouch/CanQuery, raycasts and overlap queries, mass, impulses, forces, velocity, moving assemblies, cleanup, and network ownership. Use for Roblox collisions, hit detection, RaycastParams, PhysicsService, projectiles, vehicles, knockback, constraints, deprecated BodyMovers, unstable motion, or client-owned physics exploits.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnoses macOS system-level slowness, heat and fleet-wide timeouts: high load average, leaked per-session child processes (MCP servers, helpers), fork storms, busy loops. Use when the Mac feels slow or hot, fans spin up, or everything times out at once (电脑发烫/卡顿/负载高/全部超时). Not for single-app bugs, network slowness (use tunnel-doctor), launchd watchdog design (use macos-watchdog), or disk-full (use macos-cleaner).
日本語の概要は準備中です。原文の説明を表示しています。
MUST be used first for tunnel / proxy-path connectivity failures or slow throughput (网络故障 / 连不上 / 代理或隧道下超时). Diagnoses Tailscale, proxy, TUN, DNS and SSH-tunnel problems on macOS and Windows/WSL, e.g. Tailscale ping works but SSH fails, curl works but browser gets 503, Git/Docker fails behind the proxy, or downloads crawl despite a reachable proxy. Not for application-layer bugs (use debugging-network-issues).
日本語の概要は準備中です。原文の説明を表示しています。
Help users navigate the manual, unscalable journey of finding and closing their first B2B customers. This guide focuses on leveraging personal networks, co-creating with design partners, and obsessing over early user success.
日本語の概要は準備中です。原文の説明を表示しています。
Gates whether a new test should exist and forces it to be efficient, protecting CI from low-value test bloat. Use before any change to what a pytest, Jest, or Playwright test asserts or sets up, down to one fixture or one assertion added to an existing block. Front-loads the value bar (every test must catch a realistic regression no existing test already catches; extend the nearest existing test before writing a new standalone one; test behavior through the public interface, not implementation details; collapse near-duplicates into parameterized cases) and the efficiency bar (deterministic, isolated, fast; pick the cheapest test level; Django TestCase over TransactionTestCase; no sleeps, no real network; no time bombs from absolute dates left to age against the real clock; no database a test never uses). Includes a "don't write it" decision tree. For fixing an existing flaky test use `/fixing-flaky-tests`; after this gate says a Playwright test is warranted, use `/playwright-test` for mechanics.
日本語の概要は準備中です。原文の説明を表示しています。
Infrastructure-as-code specialist for multi-cloud provisioning using Terraform across any provider (AWS, GCP, Azure, Oracle Cloud). Use for terraform plan/apply, state management, compute, databases, storage, networking, IAM, OIDC, cost optimization, policy-as-code, ISO/IEC 42001 AI controls, ISO 22301 continuity, and ISO/IEC/IEEE 42010 architecture documentation.
日本語の概要は準備中です。原文の説明を表示しています。
Create or review Terraform infrastructure and plans. Use for cloud resources, IAM, networking, state management, and infrastructure changes.
日本語の概要は準備中です。原文の説明を表示しています。
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
日本語の概要は準備中です。原文の説明を表示しています。
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building the theoretical engine of an Accounting, Organizations and Society (AOS) manuscript — choosing a social/organizational theory tradition (institutional theory, governmentality, Bourdieu, actor-network theory, practice theory, psychological process theory) and making it generate the analysis rather than decorate it. Builds the lens; it does not collect data (aos-methods) or frame the contribution (aos-contribution-framing).
日本語の概要は準備中です。原文の説明を表示しています。